Author: Yicong Lin
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
We propose two robust bootstrap-based simultaneous inference methods for time series models featuring time-varying coefficients and conduct an extensive simulation study to assess their performance. Our exploration covers a wide range of scenarios, encompassing serially correlated, heteroscedastic, endogenous, nonlinear, and nonstationary error processes. Additionally, we consider situations where the regressors exhibit unit roots, thus delving into a nonlinear cointegration framework. We find that the proposed moving block bootstrap and sieve wild bootstrap methods show superior, robust small sample performance, in terms of empirical coverage and length, compared to the sieve bootstrap introduced by Friedrich and Lin (2022) for stationary models. We then revisit two empirical studies: herding effects in the Chinese new energy market and consumption behaviors in the U.S. Our findings strongly support the presence of herding behaviors before 2016, aligning with earlier studies. However, we diverge from previous research by finding no substantial herding evidence between around 2018 and 2021. In the second example, we find a time-varying cointegrating relationship between consumption and income in the U.S.
Robust Bootstrap Inference for Linear Time-varying Coefficient Models
Author: Yicong Lin
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
We propose two robust bootstrap-based simultaneous inference methods for time series models featuring time-varying coefficients and conduct an extensive simulation study to assess their performance. Our exploration covers a wide range of scenarios, encompassing serially correlated, heteroscedastic, endogenous, nonlinear, and nonstationary error processes. Additionally, we consider situations where the regressors exhibit unit roots, thus delving into a nonlinear cointegration framework. We find that the proposed moving block bootstrap and sieve wild bootstrap methods show superior, robust small sample performance, in terms of empirical coverage and length, compared to the sieve bootstrap introduced by Friedrich and Lin (2022) for stationary models. We then revisit two empirical studies: herding effects in the Chinese new energy market and consumption behaviors in the U.S. Our findings strongly support the presence of herding behaviors before 2016, aligning with earlier studies. However, we diverge from previous research by finding no substantial herding evidence between around 2018 and 2021. In the second example, we find a time-varying cointegrating relationship between consumption and income in the U.S.
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
We propose two robust bootstrap-based simultaneous inference methods for time series models featuring time-varying coefficients and conduct an extensive simulation study to assess their performance. Our exploration covers a wide range of scenarios, encompassing serially correlated, heteroscedastic, endogenous, nonlinear, and nonstationary error processes. Additionally, we consider situations where the regressors exhibit unit roots, thus delving into a nonlinear cointegration framework. We find that the proposed moving block bootstrap and sieve wild bootstrap methods show superior, robust small sample performance, in terms of empirical coverage and length, compared to the sieve bootstrap introduced by Friedrich and Lin (2022) for stationary models. We then revisit two empirical studies: herding effects in the Chinese new energy market and consumption behaviors in the U.S. Our findings strongly support the presence of herding behaviors before 2016, aligning with earlier studies. However, we diverge from previous research by finding no substantial herding evidence between around 2018 and 2021. In the second example, we find a time-varying cointegrating relationship between consumption and income in the U.S.
Bootstrapping Trending Timevarying Coefficient Panel Models with Missing Observations
Author: Yicong Lin
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
We study a class of trending panel regression models with time-varying coefficients that incorporate cross-sectional and serial dependence, as well as heteroskedasticity. Our models also allow for missing observations in the dependent variable. We introduce a local linear dummy variable estimator capable of handling missing observations and derive its asymptotic properties. A key ingredient in our theoretical framework is a generic uniform convergence result for near-epoch processes in kernel estimation for large panels (N, T → ∞). The resulting limiting distribution reflects the pattern of missing values and depends on various nuisance parameters. An autoregressive wild bootstrap (AWB) is proposed to construct confidence intervals and bands. The AWB accommodates missing observations and automatically replicates all the nuisance parameters, demonstrating good finite sample performance. We apply our methods to investigate (i) the relationship between PM2.5 and mortality and (ii) common trends in atmospheric ethane emissions in the Northern Hemisphere. Both examples yield statistical evidence for time variation.
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
We study a class of trending panel regression models with time-varying coefficients that incorporate cross-sectional and serial dependence, as well as heteroskedasticity. Our models also allow for missing observations in the dependent variable. We introduce a local linear dummy variable estimator capable of handling missing observations and derive its asymptotic properties. A key ingredient in our theoretical framework is a generic uniform convergence result for near-epoch processes in kernel estimation for large panels (N, T → ∞). The resulting limiting distribution reflects the pattern of missing values and depends on various nuisance parameters. An autoregressive wild bootstrap (AWB) is proposed to construct confidence intervals and bands. The AWB accommodates missing observations and automatically replicates all the nuisance parameters, demonstrating good finite sample performance. We apply our methods to investigate (i) the relationship between PM2.5 and mortality and (ii) common trends in atmospheric ethane emissions in the Northern Hemisphere. Both examples yield statistical evidence for time variation.
A New Approach to Bootstrap Inference in Functional Coefficient Models
Author: Xu Fang
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Two Essays on the Moving Blocks Bootstrap and Robust Inference in Linear Regressions
Author: Bernd Fitzenberger
Publisher:
ISBN:
Category :
Languages : en
Pages : 454
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 454
Book Description
Bootstrap Inference in Time Series Econometrics
Author: Mikael Gredenhoff
Publisher: Stockholm School of Economics Efi Economic Research Institut
ISBN:
Category : Business & Economics
Languages : en
Pages : 170
Book Description
Publisher: Stockholm School of Economics Efi Economic Research Institut
ISBN:
Category : Business & Economics
Languages : en
Pages : 170
Book Description
Regression Discontinuity Designs
Author: Juan Carlos Escanciano
Publisher: Emerald Group Publishing
ISBN: 1787143902
Category : Business & Economics
Languages : en
Pages : 539
Book Description
Volume 38 of Advances in Econometrics collects twelve innovative and thought-provoking contributions to the literature on Regression Discontinuity designs, covering a wide range of methodological and practical topics such as identification, interpretation, implementation, falsification testing, estimation and inference.
Publisher: Emerald Group Publishing
ISBN: 1787143902
Category : Business & Economics
Languages : en
Pages : 539
Book Description
Volume 38 of Advances in Econometrics collects twelve innovative and thought-provoking contributions to the literature on Regression Discontinuity designs, covering a wide range of methodological and practical topics such as identification, interpretation, implementation, falsification testing, estimation and inference.
Inference of High-dimensional Linear Models with Time-varying Coefficients
Author: Yifeng He
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Modern Methods for Robust Regression
Author: Robert Andersen
Publisher: SAGE
ISBN: 1412940729
Category : Mathematics
Languages : en
Pages : 129
Book Description
Offering an in-depth treatment of robust and resistant regression, this volume takes an applied approach and offers readers empirical examples to illustrate key concepts.
Publisher: SAGE
ISBN: 1412940729
Category : Mathematics
Languages : en
Pages : 129
Book Description
Offering an in-depth treatment of robust and resistant regression, this volume takes an applied approach and offers readers empirical examples to illustrate key concepts.
Complex Systems in Finance and Econometrics
Author: Robert A. Meyers
Publisher: Springer Science & Business Media
ISBN: 1441977007
Category : Business & Economics
Languages : en
Pages : 919
Book Description
Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.
Publisher: Springer Science & Business Media
ISBN: 1441977007
Category : Business & Economics
Languages : en
Pages : 919
Book Description
Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.
Bootstrap and Inference for Some Linear Time Series Models
Author: Michael Raymond Allen
Publisher:
ISBN:
Category :
Languages : en
Pages : 220
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 220
Book Description